Autors: Manolova, A. H., Tsenov, G. T., Lazarova V., Neshov, N. N.
Title: Combined EEG and EMG fatigue measurement framework with application to hybrid brain-computer interface
Keywords: Electromyography , Electroencephalography, Fatigue, Muscles, medical signal processing, Feature extraction, Medical services

Abstract: In recent years, the EEG-based brain-computer interface has become one of the most promising areas of research in computer science and robotics. Many international research teams combining engineers and doctors, experts in neuroscience are trying to develop useful applications and devices offering disabled people to lead a normal life. Useful BCIs for disabled people suffering from Cerebral palsy, Parkinson's disease, Brain injury, Spinal cord injuries, Multiple sclerosis, Stroke, Post-polio syndrome should allow them to use all their existing brain and muscle abilities as control possibilities. In this paper we present a framework based on the mutimodal fusion approach of the user's electromyographic and electroencephalographic activities in a so called “Hybrid-BCI”. Although EEG BCI alone yields good performance as already proved in many research papers, it is outperformed by the fusion of EEG and EMG. We investigate the influence of muscular fatigue on the EMG performance.

References

    Issue

    IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), pp. 1-5, 2016, Bulgaria, IEEE, DOI 10.1109/BlackSeaCom.2016.7901569

    Copyright IEEE

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    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science